This study examined 34 lightning flashes within four separate thundersnow events derived from lightning mapping arrays (LMAs) in northern Alabama, central Oklahoma, and Washington DC. The goals were to characterize the in-cloud component of each lightning flash, as well as the correspondence between the LMA observations and lightning data taken from national lightning networks like the National Lightning Detection Network (NLDN). Individual flashes were examined in detail to highlight several observations within the dataset. The study results demonstrated that the structures of these flashes were primarily normal polarity. The mean area encompassed by this set of flashes is 375 km, with a maximum flash extent of 2300 km, a minimum of 3 km, and a median of 128 km. An average of 2.29 NLDN flashes were recorded per LMA-derived lightning flash. A maximum of 11 NLDN flashes were recorded in association with a single LMA-derived flash on 10 January 2011. Additionally, seven of the 34 flashes in the study contain zero NLDN identified flashes. Eleven of the 34 flashes initiated from tall human-made objects (e.g., communication towers). In at least six lightning flashes, the NLDN detected a return stroke from the cloud back to the tower and not the initial upward leader. This study also discusses lightning's interaction with the human built environment and provides an example of lightning within heavy snowfall observed by GOES-16's Geostationary Lightning Mapper.
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http://dx.doi.org/10.1002/2017JD027821 | DOI Listing |
Biosens Bioelectron
December 2024
Biophotonic Nanosensors Laboratory, Centro de Física Aplicada y Tecnología Avanzada (CFATA), Universidad Nacional Autónoma de México (UNAM), Querétaro, 76230, Mexico. Electronic address:
Smartphone-based colorimetric (bio)sensing is a promising alternative to conventional detection equipment for on-site testing, but it is often limited by sensitivity to lighting conditions. These issues are usually avoided using housings with fixed light sources, increasing the cost and complexity of the on-site test, where simplicity, portability, and affordability are a priority. In this study, we demonstrate that careful optimization of color space can significantly boost the performance of smartphone-based colorimetric sensing, enabling housing-free, illumination-invariant detection.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Atmospheric Physics, LAGEO, Chinese Academy of Sciences, Beijing, China.
Quickly identifying and classifying lightning waveforms is the foundation of lightning forecasting and early warning. In this paper, based on the electric field observation of the Beijing lightning location website of the Institute of Atmospheric Physics, Chinese Academy of Sciences, a recognition and classification method of pulse signal waveform based on Convolutional Neural Network(CNN) algorithm is designed and implemented. The CNN network model and its parameters were optimized from three aspects: dataset, model parameters, and network structure, achieving a recognition rate of over 90%.
View Article and Find Full Text PDFWorld J Pediatr Congenit Heart Surg
January 2025
Department of Pediatrics (Cardiology), University of Arizona, Tucson, AZ, USA.
Cardiac disease in young children can be unrecognized until symptoms are unmasked by a precipitating event, such as an infection. We present a case of anomalous left coronary artery from the pulmonary artery causing clinically significant disease in a four-month-old male with concomitant mitral regurgitation and pulmonary coccidioidomycosis who required modification of his surgical management due to the infection. This case highlights how timely diagnosis and perioperative management and recovery can be affected by concurrent infections in patients with congenital heart disease.
View Article and Find Full Text PDFNeuroimage
January 2025
Medical Physics Department, Centre François Baclesse, Caen 14000, France; CNRS, ISTCT UMR6030, GIP CYCERON, Normandie Université, Université de Caen Normandie, Caen 14000, France. Electronic address:
Rationale And Objectives: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently time-consuming. Consequently, in clinical practice, monitoring patients in clinical trials in compliance with the RANO-BM criteria is rarely achieved.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Instituto de Telecomunicações (IT), Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal.
Shrimp farming is a growing industry, and automating certain processes within aquaculture tanks is becoming increasingly important to improve efficiency. This paper proposes an image-based system designed to address four key tasks in an aquaculture tank with : estimating shrimp length and weight, counting shrimps, and evaluating feed pellet food attractiveness. A setup was designed, including a camera connected to a Raspberry Pi computer, to capture high-quality images around a feeding plate during feeding moments.
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